⚽ High-performance football analytics: build data pipelines, scrape data, model matches, rank teams, and bet smarter | Powered by www.pena.lt/y 🚀
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Updated
Jun 9, 2026 - Python
⚽ High-performance football analytics: build data pipelines, scrape data, model matches, rank teams, and bet smarter | Powered by www.pena.lt/y 🚀
AI-powered football prediction engine using probabilistic modeling, Poisson goal simulation, and tactical analysis inspired by Opta & FiveThirtyEight. Built for World Cup 2026 match forecasting, simulation, and analytics.
World Cup Predictor - Ben Jordan & Jonathan Glanfield
Football Quant - 双变量泊松+Elo+贝叶斯凯利足球量化分析框架
R codes to implement two examples for the mode and importance sampling estimation methods.
「2026世界杯预测」数据驱动的足球 AI 预测平台 · 2026 世界杯 ELO+Poisson+Monte Carlo · DeepSeek 深度研报
Bayesian Poisson and Monte Carlo simulation for an Arsenal vs PSG final.
AI-assisted football analytics and probability research platform for World Cup 2026. Analytics only, not betting advice, 18+ only.
2026 FIFA World Cup AI simulator with Poisson xG, Monte Carlo forecasting, and Streamlit dashboard.
Quantitative prediction engine for the 2026 FIFA World Cup - ELO ratings, Dixon-Coles Poisson model, Bayesian live updates, and Kelly Criterion edge analysis.
Codex skill that models any supported national-team fixture from raw results using opponent-adjusted ELO, weighted Poisson, Dixon-Coles and Monte Carlo.
Country-level determinants of the Olympic success.
Monte Carlo Poisson model for soccer match outcome probabilities, scoreline simulation, and bookmaker benchmark evaluation
Full-stack FIFA World Cup 2026 predictor — Dixon-Coles + EA FC 26 player ratings + real fatigue data, 100k parallel Monte-Carlo simulations of the official 48-team bracket, with a live-results mode that re-simulates as the real tournament unfolds.
Expected-points World Cup score-prediction optimiser using market-implied probabilities and historical validation.
Enjoyment-first 2026 World Cup daily digest: LLM tactical briefs x Dixon-Coles x market baseline, pushed to Telegram nightly
Material for Lab 12 for the course
Three studies using R: 1️⃣ Child malformation risk (logit/probit models) linked to maternal alcohol. 2️⃣ Student awards (Poisson) driven by academic programs & math scores. 3️⃣ Soccer arrests (Negative Binomial) reduced by social investment. Code includes EDA, model comparisons (AIC/BIC), and regression workflows.
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